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1 United Nations Conference on Trade And Development A PRELIMINARY ANALYSIS ON NEWLY COLLECTED DATA ON NON-TARIFF MEASURES POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES STUDY SERIES No. 53

2 UNITED NATIONS CONFERENCE ON TRADE AND DEVELOPMENT POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES STUDY SERIES No. 53 A PRELIMINARY ANALYSIS ON NEWLY COLLECTED DATA ON NON-TARIFF MEASURES by Alessandro Nicita UNCTAD, Geneva and Julien Gourdon CEPII, Paris UNITED NATIONS New York and Geneva, 2013

3 NOTE The purpose of this series of studies is to analyse policy issues and stimulate discussions in the area of international trade and development. The series includes studies by UNCTAD staff, as well as by distinguished researchers from other organizations and academia. In keeping with the objective of the series, authors are encouraged to express their own views, which do not necessarily reflect the views of the UNCTAD secretariat or its member States. The designations employed and the presentation of the material do not imply the expression of any opinion whatsoever on the part of the United Nations Secretariat concerning the legal status of any country, territory, city or area, or of its authorities, or concerning the delimitation of its frontiers or boundaries. Material in this publication may be freely quoted or reprinted, but acknowledgement is requested, together with a reference to the document number. It would be appreciated if a copy of the publication containing the quotation or reprint were sent to the UNCTAD secretariat at the following address: Chief Trade Analysis Branch Division on International Trade in Goods and Services, and Commodities United Nations Conference on Trade and Development Palais des Nations CH-1211 Geneva Switzerland Series editor: Victor Ognivtsev Officer-in-Charge, Trade Analysis Branch UNCTAD/ITCD/TAB/54 UNITED NATIONS PUBLICATION ISSN Copyright United Nations 2013 All rights reserved ii

4 ABSTRACT This paper makes use of data newly collected by UNCTAD and the World Bank to investigate the use of non-tariff measures (NTMs) in about 26 countries. The analysis is based on simple inventory methods: frequency indices and coverage ratios. The results indicate that the use of NTMs is extensive and increasing, especially with regard to technical measures. Technical barriers to trade (TBTs) are found to affect a large share (about 30 per cent) of international trade. Given the more limited scope for sanitary and phytosanitary (SPS) measures, these affect only about 15 per cent of trade but more than 60 per cent of agricultural products. In regard to non-technical measures, their use varies greatly across countries and economic sectors. The use of quantity controls has increased but is now largely limited to non-automatic licences. As a whole, quantity control measures affect approximately 16 per cent of products and 20 per cent of trade. Pre-shipment inspection requirements affect about 11 per cent of trade. These are implemented especially in low-income countries to help custom administrations in the correct evaluation of imports and their proper taxation. Price-control measures are only rarely used and affect less than 5 per cent of trade and only 2 per cent of products. The results also suggest the presence of correlation between the use of NTMs and traditional forms of trade policy. This may indicate that NTMs have been used, at least to some degree, as substitutes to tariffs in order to continue protecting key economic sectors in spite of the tariff liberalization of the last 10 years. Key words: non-tariff measures; trade policy; market access JEL Classification: F1 iii

5 ACKNOWLEDGEMENTS The authors would like to thank Marc Bacchetta, Olivier Cadot, Aki Kuwahara and Mariem Malouche for useful comments and discussion. Any mistakes or errors remain the authors own. iv

8 1. Introduction Since the paper The case of the missing trade and other mysteries (Trefler, 1995), many studies have investigated the reasons why world trade is not as large as economic models predict. One of the most compelling explanations was provided by Obstfeld and Rogoff (2000), who suggested that large unobserved trade costs may explain most of the discrepancies between model estimates and trade statistics. The presence of hidden costs was supported by subsequent work, as in Anderson and Van Wincoop (2004), whose research indicated that the costs associated with cross-border trade, even between well-integrated countries, are well above those that can be explained by geographic distance and traditional trade policies. Although a number of studies have attempted to capture and quantify the impact of some of the hidden costs of trading (Maskus et al., 2005; Djankov et al., 2010; Hoekman and Nicita, 2011), these attempts are greatly constrained by the available data. The existing data on trade costs are largely related to tariffs, and only a few databases provide information on NTMs and behindthe-border trade costs (for example, the Doing Business database, the Trade Facilitation Database, the Logistic Performance Index, and the UNCTAD Trade Analysis and Information System (TRAINS) database). Moreover, most of the existing data are too aggregated to be utilized for detailed policy analysis and often only provides information on the effects of trade impediments rather than on the impediments themselves. In practice, the analysis must compromise in terms of policy coverage, focusing on the aggregate effects of the few countries or sectors where the data are available. A particularly relevant issue for both researchers and policymakers is related to the impact of NTMs on trade. There are several reasons to focus attention on NTMs as one of the main sources of trade costs. One reason is that their impact on trade is still poorly understood and not easily measured, encompassing a wide set of policies that can have very diverse effects. For example, requirements concerning marking, labelling and packaging, although adding to the costs of production, are not generally discriminatory and have low compliance costs, and thus have relatively unimportant effects on trade. On the other hand, quotas, voluntary export restraints and non-automatic import authorizations often have much more significant effects. A second reason to examine NTMs is their proliferation. While there exists a long history of application of NTMs, 1 the use of such measures to regulate trade has been rising since the 1990s both in terms of countries adopting such measures as well as in their variety. A third reason is that NTMs can be discriminatory: even when they are indiscriminately applied to all imported goods, many NTMs discriminate among a country's trading partners because the costs of compliance are often different across exporters. Compliance costs are generally higher in low-income countries, as NTM-related production processes and export services are often more expensive, or need to be outsourced abroad. Another reason to investigate NTMs is that they could be protectionist. Governments are using increasingly sophisticated methods about how they protect domestic industries. While trade barriers have historically taken more obvious forms, such as tariffs or quotas, different forms are emerging which are harder to identify and quantify. A mounting concern is that liberalization in tariffs may be countered by the increasing number of restrictive NTMs. Broadly defined, NTMs include all policy-related trade costs incurred from production to the final consumer, with the exclusion of tariffs. For practical purposes NTMs are categorized according to their scope and/or design and are broadly distinguished as technical (SPS measures and TBTs) and nontechnical. These are further distinguished as hard measures (for example, price and quantity control), threat measures (for example, anti-dumping measures and safeguards), and others such as trade-related finance and investment measures. In practice, NTMs have the potential to substantially distort international trade, whether their trade effects are protectionist or not. For example, measures such as 1 For example, English laws in the seventeenth and eighteenth centuries required that all colonial trade be conducted on British ships manned by British sailors. Also, certain goods had to be shipped to Great Britain first before they could be sent to their final destination. 1

9 quality standards, although generally imposed without protectionist intent, may be of particular concern to poor countries whose producers are often ill-equipped to comply with them. The paucity of data on trade policy measures has been the main problem behind the study of the effect of NTMs on trade. Seemingly simple questions regarding what policy measures are imposed by countries, and what types of measures are faced by particular products cannot be answered for most goods and countries because of the lack of detailed information. The fact that NTMs are increasingly used to regulate international trade makes the need to update data even more compelling. The reason behind the scarcity of databases on NTMs is largely related to the difficulty in collecting the data and in assembling a consistent cross-country database. Unlike tariffs, NTM data are not merely numbers; the relevant information is often hidden in legal and regulatory documents. Moreover, these documents are generally not centralized but often reside in different regulatory agencies. All these issues make the collection of NTM data a very resource-intensive task. The first attempt to collect and categorize NTMs was conducted by UNCTAD in the late 1990s, and the data are available in the UNCTAD TRAINS database accessible via the World Bank World Integrated Trade Solution (WITS) software. 2 However, the TRAINS database has not been consistently updated in the last 10 years. To fill this gap and in response to the increased interest of both researchers and policymakers, UNCTAD and the World Bank, in collaboration with the International Trade Centre and the African Development Bank, have initiated a new effort on NTMs data with the objectives of improving the coverage and classification of NTMs and of updating, consolidating and freely disseminating NTM data. As of early 2011, this joint effort has produced an updated NTMs classification as well as detailed new data for approximately 25 countries, with data from more countries in the pipeline. This present paper makes use of the new data to provide some preliminary information on the incidence of NTMs across countries and by economic sector and type of NTMs. Given limited coverage of the new data, the analysis is mainly descriptive in nature and employs simple indicators (an inventory approach based on frequency and coverage ratio) rather than trying to produce more complex measures such as price gaps or ad valorem equivalents. In practice, the analysis focuses on the identification of the relative use of various types of NTMs and their incidence across countries and products. The study is organized as follows: section 2 provides some details on the definition and classification of NTM data, while the bulk of the descriptive analysis is contained in section 3. In section 3 we provide descriptive statistics on the incidence of NTMs in terms of frequency (number of product lines exposed to NTMs) and coverage (share of total imports exposed to NTMs). In so doing, we analyse differences both in terms of countries and product groups. We also examine the evolution in the use of NTMs by using original data from the TRAINS database and comparing them with the data collected recently. Section 4 explores the relationship between NTMs and traditional forms of trade policy. The last section summarizes the main findings and offers some policy conclusions. 2 See 2

10 2. Definition, classification and data collection The definition of NTMs should encompass all measures altering the conditions of international trade, including policies and regulations that restrict trade as well as those that facilitate it. It is frequent that NTMs are incorrectly referred to as non-tariff barriers (NTBs). The difference between the two terms is that NTMs comprise a wider set of measures than NTBs, the latter term being now generally only used to describe discriminatory NTMs imposed by governments to favour domestic over foreign suppliers. The cause of this confusion is because in the past most NTMs were largely in the form of quota or voluntary export restraints. These measures are restrictive by design, which explains why the term barrier was used. In present times, policy interventions take many more forms, and it is therefore preferable to refer to them as measures instead of barriers, to underline that the measure may not necessarily be welfare or trade reducing. 3 For practical purposes, the commonly used definition of NTMs is (UNCTAD, 2010): Non-tariff measures (NTMs) are policy measures, other than ordinary customs tariffs, that can potentially have an economic effect on international trade in goods, changing quantities traded, or prices or both. This definition is broad and to a large extent uninformative as it was in the case of NTBs, which were defined as policies that are not tariffs. To better identify NTMs, and to distinguish among their various forms, a detailed classification is therefore of critical importance. To facilitate data collection and analysis, the multitude of NTMs are often aggregated into various groups, as already mentioned in the introduction. In more detail, these include hard measures (for example, measures of price and quantity control), threat measures (for example, anti-dumping measures and safeguards), SPS measures, TBTs, and other categories such as export measures, trade-related investment measures, distribution restrictions, restrictions on post-sales services, subsidies, measures related to intellectual property rights and rules of origin. Each of these groups comprises various and often very different forms of NTMs. The classification proposed by UNCTAD and agreed by the Group of Eminent Persons on Non-tariff Barriers takes this into account and develops a tree/branch structure where measures are categorized into chapters depending on their scope and design. Each chapter is then further differentiated into sub-groups to allow a finer classification of the regulations affecting trade. In practice, the NTMs classification encompasses 16 chapters (A to P) (see figure 1) and each individual chapter is divided into groupings with depth of up to three levels (one, two, and three digits). Although a few chapters reach the threedigit level of disaggregation, most of them stop at two digits. The complete classification can be found in UNCTAD (2010). Each chapter of the classification comprises measures with similar purposes. All chapters reflect the requirements of the importing country concerning its imports, with the exception of measures imposed on exports (chapter P). The effect on trade of each group of measures varies considerably. While some groups of NTMs have clear restrictive impacts, others produce uncertain effects. For example, the measures under chapters (A) to (C) have a relatively clear relationship with the market imperfections they try to address (Beghin, 2006). These measures are largely regulatory policies in response to a variety of concerns raised by society in many areas such as the environment, animal welfare, food safety and consumer rights. The policies are not necessarily restrictive because they can also enhance consumer demand for goods by increasing quality attributes (technical requirements) or by 3 For example, NTMs such as standards and regulations may expand trade by facilitating production and exchange of information, reducing transactions costs, guaranteeing quality, and achieving the provision of public goods (Maskus, Wilson and Otsuki 2003). Where trade in some products would have been difficult without clear standards, with it, trade could be created between two countries. 3

11 reducing informational asymmetries (standards). However, many of these policies involve considerations of institutional capacity and are likely to have distortionary impacts on trade. Sometimes they are imposed to address the possible capacity failures of trade partners; often they require an extensive domestic institutional capacity to be implemented. Although different types of requirements affect different inputs and stages of production, most of these policies also affect overall trade costs (for example, certification, inspections, and the like). In addition, compliance costs often vary depending on the infrastructure and institutional capacity of the exporting country, and thus ultimately these costs do affect trade flows. Figure 1. NTM classification Chapter Technical measures A B Sanitary and phytosanitary measures (SPS) Technical barriers to trade (TBT) C Pre-shipment inspection and other formalities D Price control measures Import measures Nontechnical measures E F G H I Licenses, quotas, prohibition and other quantity control measures Charges, taxes and other para-tariff measures Finance measures Anti-competitive measures Trade-related investment measures J Distribution restrictions K Restrictions on post-sales services L Subsidies (excluding export subsidies) M Government procurement restrictions N Intellectual property O Rules of origin Export measures P Export-related measures (including export subsidies) While the intent and scope of NTMs vary considerably, their effect on trade is generally more understood and easier to quantify. The effects of price-control measures are relatively simple to quantify, especially anti-dumping and safeguards. Quantity control instruments have been extensively examined in the analysis of quotas, tariff rate quotas and their administration (see Boughner et al., 2000). Paratariff measures can be analysed as conventional tax instruments and their incidence is straightforward to perceive. Financial, anti-competitive, and trade-related investment measures have indirect effects on trade, and their actual impact is more difficult to assess. The box following provides some more details on the measures contained in each chapter. 4

12 Brief description of NTM chapters Chapter A, on SPS measures, refers to measures affecting areas such as restriction of substances, and measures for preventing dissemination of disease. Chapter A also includes all conformity assessment measures related to food safety, such as certification, testing and inspection, and quarantine. Chapter B, on technical measures, refers to measures such as labelling, other measures protecting the environment, standards on technical specifications, and quality requirements. Chapter C classifies the measures related to pre-shipment inspections and other customs formalities. Chapter D, price-control measures, includes measures that are intended to change the prices of imports, such as minimum prices, reference prices, anti-dumping or countervailing duties. Chapter E, licensing, quotas and other quantity control measures, groups the measures that have the intention to limit the quantity traded, such as quotas. Chapter E also covers licences and import prohibitions that are not SPS or TBT related. Chapter F, on charges, taxes and other para-tariff measures, refers to taxes other than custom tariffs. Chapter F also groups additional charges such as stamp taxes, licence fees, statistical taxes, and also decreed customs valuation. Chapter G, on finance measures, refers to measures restricting the payments of imports, for example when the access and cost of foreign exchange is regulated. The chapter also includes measures imposing restrictions on the terms of payment. Chapter H, on anticompetitive measures, refers mainly to monopolistic measures, such as state trading, sole importing agencies, or compulsory national insurance or transport. Chapter I, on trade-related investment measures, groups the measures that restrict investment by requiring local content, or requesting that investment should be related to export in order to balance imports. Chapter J, on distribution restrictions, refers to restrictive measures related to the internal distribution of imported products. Chapter K, on the restriction on post-sales services, refers to difficulties in allowing technical staff to enter the importing country to provide accessory services (for example, the repair or maintenance of imported technological goods). Chapter L, contains measures that relate to the subsidies that affect trade. Chapter M, on government procurement restriction measures, refers to the restrictions bidders may find when trying to sell their products to a foreign government. Chapter N, on intellectual property measures, refers to problems arising from intellectual property rights. Chapter O, on rules of origin, groups the measures that restrict the origins of products, or their inputs. Chapter P, on export measures, groups the measures a country applies to its exports. It includes export taxes, quotas or prohibitions, and the like. 5

13 The classification discussed above greatly simplifies the data collection. However, being able to classify laws and regulations into the appropriate NTM category is only part of the challenge in assembling a database of NTMs. Besides a proper classification, one of the problems related to data collection is that, in most cases, there is not one sole national repository agency of NTMs data, as laws and regulations affecting trade are often promulgated by different government agencies and regulatory bodies, making the assembly of an exhaustive NTMs database quite a challenging task. In practice, the data have to be carefully scrutinized for possible duplications, omissions, or any other problems in order to minimize inaccuracies. This paper provides an analysis based on the newly collected NTM data comprising 24 developing countries plus the European Union and Japan. The data cover measures from chapters A to I, and chapter P. 4 The data follow the Harmonized System (HS) classification at the six-digit level covering more than 5,000 different products. 3. The incidence of NTMs There are various approaches to identify the importance of trade measures and assessing their effects on international trade. Methodologies include simple inventory measures, computation of price gaps and the estimation of ad valorem equivalents. As the intent of this paper is mainly to explore the collected data, the simple inventory approach is used. This approach is based on two indices: the frequency index and the coverage ratio. The frequency index simply captures the percentage of products that are subject to one or more NTMs. The coverage ratio captures the percentage of imports that are subject to one or more NTMs. The frequency index accounts only for the presence or absence of an NTM, and summarizes the percentage of products to which one or more NTMs are applied. In more formal terms, the frequency index of NTMs imposed by country j is calculated as: F j = D im i 100 M i (1) where D is a dummy variable reflecting the presence of one or more NTMs and M indicates whether there are imports of product i (also a dummy variable). Note that frequency indices do not reflect the relative value of the affected products and thus cannot give any indication of the importance of the NTMs on overall imports. A measure of the importance of NTMs on overall imports is given by the coverage ratio, which measures the percentage of trade subject to NTMs for the importing country j. In formal terms the coverage ratio is given by: C j = DV i i 100 Vi (2) 4 Because of objective difficulties in the collection of data on some measures, data covering measures from chapters J to O were not actively collected. 6

14 where D is defined as before and V is the value of imports in product i. One drawback of the coverage ratio, or any other weighted average, arises from the likely endogeneity of the weights (the fact that imports are dependent on NTMs). This problem is best corrected by using weights fixed at trade levels that would arise in an NTM- (and tariff-) free world. Otherwise, the coverage ratio would be systematically underestimated. While one cannot achieve that benchmark, it is possible to soften the endogeneity problem (and test the robustness of the results) by using trade values of past periods. We start the descriptive analysis by aggregating all the data collected and examining the incidence of various types of NTMs. Figure 2 illustrates the distribution of NTMs across five main chapters for the 26 countries examined so far. For each chapter both the frequency indices and coverage ratios are reported. Figure 2. Frequency index and coverage ratios by chapter, all countries Percentage Frequency ratio Coverage ratio A: SPS B: TBT C: Pre-shipment D: Price control E: Quantity control According to the newly collected data, TBTs are by far the most widely used regulatory measures, with about 30 per cent of products and trade values affected. Quantity controls affect about 16 per cent of products and 20 per cent of trade. Slightly less than 15 per cent of trade is affected by SPS measures. The large incidence of SPS measures and TBTs raises concerns for developing countries exports. These measures impose quality and safety standards that often exceed multilaterally accepted norms. Although these measures are not protectionist in nature they often result in diverting trade from developing countries where the production process and certification bodies are often inadequate. Moreover, the cost of compliance with SPS measures and TBTs is often higher in low-income countries as infrastructure and export services are often more expensive or need to be outsourced abroad. In practice, SPS measures and TBTs may erode the competitive advantage that developing countries have in terms of labour costs and preferential access. Among non-technical measures, pre-shipment inspections affect approximately 11 per cent of trade and products. Although pre-shipment inspections are often necessary to provide some assurance on the quality/quantity of the shipment, which may thus promote international trade, they add to the cost of trading. These additional costs may reduce the competitiveness of countries, thus distorting trade. Concerning price-control measures (5 per cent of trade and only 2 per cent of products), these constitute one of the least-used forms of NTMs. Price-control measures affect only a small share of goods and are largely related to anti-dumping and countervailing duties, as well as some form of administrative pricing for staple food, energy and other sensitive sectors. Finally, quantitative measures still affect about 20 per 7

15 cent of international trade. Only a small percentage of these measures still take the form of quotas and export restrictions, since most these quantitative restrictions are illegal under World Trade Organization (WTO) rules. Most of the measures are in the form of non-automatic licensing, often necessary to administer the importation of goods where SPS- and TBT-related issues are of particular importance. Some quantitative restrictions such as quotas, prohibitions and export restraints are in place, but are largely limited to a number of sensitive products. The incidence of different forms of NTMs varies across geographic areas. Although SPS measures and TBTs are used extensively among the countries in our sample, Latin American and African countries also implement a large number of quantitative restrictions. In general, African countries appear to regulate their imports relatively more than many other countries. Although this may seem surprising, it may result, at least in the case of SPS measures and TBTs, from an effort to harmonize regulations with their main trading partner, the European Union. The reason behind this relatively large number of pre-shipment inspections is that these are often implemented to fight corruption, to facilitate and accelerate custom procedures, and ultimately to help in the correct evaluation of imports and their proper taxation. Figure 3. Frequency index and coverage ratios by chapter, by region Latin America Asia Africa High income TBT SPS Pre-shipment Quantity control Price control TBT SPS Pre-shipment Quantity control Price control TBT SPS Pre-shipment Quantity control Price control TBT SPS Pre-shipment Quantity control Price control Coverage ratio Frequency index The use of NTMs varies considerably not only across regions but more so between countries. Figure 3 summarizes the data collected so far in terms of frequency index and coverage ratio for each country for all NTMs as a whole. On average, countries apply some form of NTMs for slightly less than half of the approximately 5,000 products included in the HS six-digit classification. This figure varies greatly by country. While Egypt, Uganda, Kenya, Argentina and the European Union have many products covered by at least one NTM, NTMs are applied only to a subset of products in Peru, Uruguay, 8

16 the United Republic of Tanzania and the Plurinational State of Bolivia. Although this large variance may be due to some extent to different primary data collection methods, this is likely to explain only part of the differences, as a large variance is also found for Latin American countries whose data are collected by the same agency the Associação Latinoamericana de Integração. The large differences found among Latin American countries are also found in other regions. In Africa the frequency index varies from 90 per cent in Burundi and Uganda to about 10 per cent of Senegal and Tanzania. Such large differences suggest that the use of NTMs varies greatly across countries, even within the same geographic areas (figure 4). Figure 4. Frequency indices and coverage ratios, by country 9

17 Similar conclusions can be reached by looking at coverage ratios (the percentage of imports subject to NTMs) as these are found to be highly correlated with frequency indices. Although correlated, coverage ratios are often larger than frequency indices. A coverage ratio relatively higher than the frequency index can be explained by two factors. The first is import composition. Countries, especially low-income countries, often import larger volumes of products where NTMs are more extensively used (agriculture). The second factor is a larger use of NTMs policies on products that are most traded (for example, for consumer protection). This is often the case in developed countries. The incidence of the use of NTMs depends on both the percentage of products (or imports) affected by NTMs, and the number of NTMs affecting each product. The frequency and coverage ratios illustrated above do not take into account whether more than one type of NTM is applied to the same product. In practice, a large number of products have more than one regulatory measure applied to them. For example, a product could be subject to a sanitary standard (chapter A) as well as a technical measure on quality (chapter B), and finally to some licensing (chapter E). Arguably, the greater the number of NTMs applied to the same product, the more regulated the commerce of that product is, especially if measures are from different chapters. The rationale is that measures within the same chapter are similar in nature and thus often impose relatively less burden than measures from different chapters. To better illustrate the pervasiveness of NTMs, figure 5 reports the number of products affected by one, two or three types of NTMs, where types are differentiated by chapter. Although the majority of products affected by NTMs are concerned by only one chapter, a substantial number of countries apply NTMs from multiple chapters to many products. As the pervasiveness of NTMs depends also on the number affecting each product, this approach allows a better comparison across countries. For example, among the 4,550 products on which the European Union imposes NTMs, about 3,200 are subject to NTMs from only one chapter, about 1,100 are affected by NTMs from two different chapters, and about 250 by NTMs from three or more chapters. Although the European Union frequency index and coverage ratio are similar to those of Argentina, European Union imports can be considered relatively less regulated, as the majority of imports to Argentina are affected by NTMs from two or more chapters. These statistics also allow us to verify the quality of the data. The case of Namibia (and possibly also of Uganda) is particularly striking as all 2,900 products on which NTMs are applied are subjected to multiple forms from at least three different chapters. However, as this is unlikely to be the case, the data from Namibia need to be further scrutinized for possible errors in the classification procedure. 10

18 Figure 5. Number of products affected by number of NTM chapters Number of products Burundi Egypt Kenya Madagascar Mauritius Morocco Namibia Senegal South Africa United Republic of Tanzania Tunisia Uganda Bangladesh Cambodia Indonesia Lao People's Democratic Republic Lebanon Philippines Syrian Arab Republic Argentina Plurinational State of Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay European Union Japan Africa Asia Latin America High Income 1 type 2 types 3 types 4 types It is often the case that countries apply a wide number of NTMs within each chapter. For example, one specific product may be subject to geographical restriction, labelling, fumigation and some conformity assessments, which all fall under the SPS measures chapter A. Although some of these measures may impose few additional costs, some others are quite distinct. A large number of measures within a chapter could imply an even stricter regulatory framework. Thus, it is important to provide some information on the actual number of NTMs applied to single products. This information is given by simply calculating the average number of NTMs applied to each HS six-digit product. Table 1 reports for each country the average number of NTMs applied to the products facing at least one NTM at the various levels of aggregation of classification. 11

19 Table 1. Use of multiple types of NTMs at different levels of aggregation Average over number of lines with NTMs Number of lines with at least one NTM Chapter level One-digit level All types of NTMs Argentina Bolivia, Plurinational State of Brazil Cambodia Chile Colombia Ecuador Egypt European Union Indonesia Japan Kenya Lao People s Democratic Republic Lebanon Madagascar Mauritius Mexico Morocco Namibia Paraguay Peru Philippines Senegal Syrian Arab Republic Tunisia Uganda United Republic of Tanzania Uruguay Venezuela, Bolivarian Republic of Average (simple) With very few exceptions, products are rarely affected by only one type of NTM because several regulatory measures are often applied in parallel. The average number of NTMs affecting products facing at least one NTM is 1.66 at the chapter level, 2.61 at the one-digit level, and 3.38 when all possible NTMs are considered. These figures vary considerably across countries. For example, while Mauritius imposes about one NTM measure at the chapter level for each of its 2,354 HS six-digit products covered by NTMs, Namibia imposes an average of more than nine NTMs from about four different chapters on 2,858 HS six-digit goods. Similarly, Tunisia applies on average 11 different NTMs from two different chapters on each of its 1,166 products, while Egypt applies less than two types to its 5,006 products. Although these statistics provide valuable information, such large differences at the three-digit level should not be considered as proof of overregulated import regimes, because the discrepancies could also be due to data availability and collection procedures. In particular, differences may be related to whether the document is detailed enough to distinguish among several types of similar NTMs, in which case the measures are generally classified only under broader codes. Differences at the 12

20 x one-digit level often reflect real differences in the use of regulatory measures for imports, and thus can provide a better assessment of the regulatory regime. For example, both Mexico and Brazil impose some form of NTM for about 3,000 products. However, while Mexico applies on average only 1.6 one-digit NTM measure on each of these products, Brazil applies about 3.1. Arguably, imports into Brazil can be considered on average to be more regulated than those of Mexico. As NTMs regulate different aspects of the production and trade of goods, it is often the case that various types of NTMs are applied in parallel to the same product. While in most cases NTMs are used complementarily and applied simultaneously to the same product for technical or procedural reasons, there are other cases where NTMs are applied in parallel to further insulate domestic industries from foreign competition. To explore to what extent the various types of NTMs are complementary, we have calculated correlation coefficients among one-digit NTMs. Figure 6, showing correlation statistics, suggests several key patterns in the concurrent use of various types of NTMs. First, several SPS measures are often applied in parallel for example, tolerance limits (A2) are often used in conjunction with labelling (A3) and hygienic requirements (A4) and also with treatment measures such as fumigation (A5) and conformity assessments (A8). Second, SPS measures are also often paired with TBTs (B5). This is largely related to regulation on genetically modified organisms. SPS measures are also found to be correlated to direct consignment (C2), and to requirements to pass through specified custom ports (C3). This is possibly to facilitate the inspections and traceability of agricultural products. For similar reasons SPS measures are also correlated with non-automatic licensing (E1). It is found that TBTs are relatively less correlated with other groups of NTMs. The only exceptions are the TBTs on production or post-production requirement (B4) which are often used simultaneously with price controls (D4, D5 and D6) and quantity controls (E2 and E3). As there is no clear explanation why such NTMs should be correlated, it would be interesting to further explore this pattern. We leave this, however, for future research. Finally, and not surprisingly, quantity and pricecontrol measures appear closely interrelated. This specifically concerns quantity control quota (E2) and prohibition (E3) and price-control measures anti-dumping (D4) and countervailing (D5) measures. All these measures are often used concomitantly to reinforce the protection of specific sectors. Figure 6. Correlation of different one-digit NTMs E3 E2 E1 D6 D5 D4 D3 D1 C9 C4 C3 C2 C1 B8 B7 B6 B5 B4 B3 B2 B1 A8 A7 A6 A5 A4 A3 A2 A1 A1 A2 A3 A4 A5 A6 A7 A8 B1 B2 B3 B4 B5 B6 B7 B8 C1 C2 C3 C4 C9 D1 D3 D4 D5 D6 E1 E2 E3 y 13

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